Shi-Feng Sun (Monash University, Australia), Ron Steinfeld (Monash University, Australia), Shangqi Lai (Monash University, Australia), Xingliang Yuan (Monash University, Australia), Amin Sakzad (Monash University, Australia), Joseph Liu (Monash University, Australia), ‪Surya Nepal‬ (Data61, CSIRO, Australia), Dawu Gu (Shanghai Jiao Tong University, China)

In Dynamic Symmetric Searchable Encryption (DSSE), forward privacy ensures that previous search queries cannot be associated with future updates, while backward privacy guarantees that subsequent search queries cannot be associated with deleted documents in the past. In this work, we propose a generic forward and backward-private DSSE scheme, which is, to the best of our knowledge, the first practical and non-interactive Type-II backward-private DSSE scheme not relying on trusted execution environments. To this end, we first introduce a new cryptographic primitive, named Symmetric Revocable Encryption (SRE), and propose a modular construction from some succinct cryptographic primitives. Then we present our DSSE scheme based on the proposed SRE, and instantiate it with lightweight symmetric primitives. At last, we implement our scheme and
compare it with the most efficient Type-II backward-private scheme to date (Demertzis et al., NDSS 2020). In a typical network environment, our result shows that the search in our scheme outperforms it by 2-11x under the same security notion.

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GALA: Greedy ComputAtion for Linear Algebra in Privacy-Preserved Neural...

Qiao Zhang (Old Dominion University), Chunsheng Xin (Old Dominion University), Hongyi Wu (Old Dominion University)

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PGFUZZ: Policy-Guided Fuzzing for Robotic Vehicles

Hyungsub Kim (Purdue University), Muslum Ozgur Ozmen (Purdue University), Antonio Bianchi (Purdue University), Z. Berkay Celik (Purdue University), Dongyan Xu (Purdue University)

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Taking a Closer Look at the Alexa Skill Ecosystem

Christopher Lentzsch (Ruhr-Universität Bochum), Anupam Das (North Carolina State University)

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Towards Understanding and Detecting Cyberbullying in Real-world Images

Nishant Vishwamitra (University at Buffalo), Hongxin Hu (University at Buffalo), Feng Luo (Clemson University), Long Cheng (Clemson University)

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Privacy Starts with UI: Privacy Patterns and Designer Perspectives in UI/UX Practice

Anxhela Maloku (Technical University of Munich), Alexandra Klymenko (Technical University of Munich), Stephen Meisenbacher (Technical University of Munich), Florian Matthes (Technical University of Munich)

Vision: Profiling Human Attackers: Personality and Behavioral Patterns in Deceptive Multi-Stage CTF Challenges

Khalid Alasiri (School of Computing and Augmented Intelligence Arizona State University), Rakibul Hasan (School of Computing and Augmented Intelligence Arizona State University)

From Underground to Mainstream Marketplaces: Measuring AI-Enabled NSFW Deepfakes on Fiverr

Mohamed Moustafa Dawoud (University of California, Santa Cruz), Alejandro Cuevas (Princeton University), Ram Sundara Raman (University of California, Santa Cruz)